Systems for allocating multi-function resources in a process system and methods of operating the same

ABSTRACT

There are disclosed systems, as well as methods of operation, for allocating multi-function resources among a plurality of tasks within a process system. An exemplary resource allocator is introduced that allocates multi-function resources among tasks within a process system capable of executing at least one application process. The resource allocator comprises a monitoring controller, model of the process system and a resource allocation controller. The monitoring controller monitors measurable characteristics associated with the executing application process, multi-function resources and tasks, each of the measurable characteristics being one of a status characteristic and a logistical characteristic. The model represents mathematically the multi-function resources and the tasks, and defines relationships among related ones thereof as a function of the application process. The resource allocation controller operates the model in response to the monitored measurable characteristics and allocates ones of the multi-function resources among ones of the tasks within the process system to efficiently execute the at least one application process.

This application claims priority to U.S. Provisional Patent ApplicationSer. No. 60/408,817 filed Sep. 6, 2002. This application is commonlyowned by the assignee of this patent document. This application isincorporated by reference for all purposes as if fully set forth herein.

TECHNICAL FIELD OF THE INVENTION

The present invention is directed generally to resource allocationsystems and process control systems and, more specifically, to systemsand methods for allocating a plurality of multi-function resources amonga plurality of tasks within a process system.

BACKGROUND OF THE INVENTION

Allocation of multi-function resources within resource allocation andprocess control systems may be thought of as the management (i.e.,administration, command, control, direction, governance, monitoring,regulation, etc.) of such multi-function resources (e.g., manufacturingtools, instruments, hardware, software, databases,communication/connectivity resources, transportation resources,facilities, utilities, inventories, etc.) among a variety of taskswithin a process system.

Process systems may be arranged and implemented to manage largefacilities, such as a manufacturing plant, a semiconductor fabricationfacility, a mineral or crude oil refinery, or the like, as well asrelatively smaller facilities, such as a corporate communicationsnetwork, a data repository and management system, or the like. Suchsystems may be distributed or not, and typically include numerousmodules tailored to manage various associated processes, whereinconventional means link these modules together to produce thedistributed nature of the process system. This affords increasedperformance and a capability to expand or reduce the process system tosatisfy changing needs.

Process systems are developed and tailored to satisfy wide ranges ofprocess requirements, whether local, global or otherwise, and regardlessof facility type. Such developers and users of such systems commonlyhave two principle objectives: to (i) centralize management/control ofas many sub-processes or processes as possible to improve overallefficiency and (ii) support a common interface that communicates dataamong various modules managing/controlling or monitoring the processes,and also with any such centralized controller.

Each process, or group of associated sub-processes or processes, hascertain input (e.g., data, diagnostics, feed, flow, power, etc.) andoutput (e.g., data, pressure, temperature, utilization parameters, etc.)characteristics associated therewith. These characteristics aremeasurable, and may be represented in a discernable manner.

Predictive control methodologies/techniques may be used to optimizecertain processes as a function of such characteristics. Predictivecontrol techniques may use algorithmic representations to estimatecharacteristic values (represented as parameters, variables, etc.)associated with them that can be used to better manage such processresources among a plurality of tasks.

Such optimization efforts only account mathematically for the tasksbeing performed and the process resources then used to resolve the samebased upon statistical characteristics only, thereby failing to modeland factor into the optimization effort both status and logistical data,as well as to account for human capabilities and interaction (i.e.,functions, skills, qualifications, task preferences, track records andthe Like) that ultimately utilize the process resources to resolve thetasks. Conventional approaches can exhibit poor response to constantlychanging or exigent circumstances, and as such fail to cooperativelyoptimize process resources, particularly process resources capable ofperforming multiple functions. What is needed in the art is a powerfuland flexible means for dynamically analyzing and modifying processstatus in a real-time mode through allocation and reallocation ofmultifunction process resources among a plurality of tasks within aprocess system.

Using semiconductor fabrication as an example, in order to provideshortest cycle times, highest quality, timely-delivered cost-effectiveproducts that meet revenue growth plans, there is a continuous need toimprove manufacturing processes and sub-processes, including the contentand methods of delivering information to the operations staff.

Information about manufacturing tools and work in process inventory arecritical to the decision making process necessary to operate asemiconductor wafer manufacturing line. With complex multi-tool,multi-technology, multi-product resources (“multi-function resources”),a need exists in the industry for a system and method that allocate suchmulti-function resources among a plurality of tasks within fabricationfacility so as to execute a flexible process or plan that responds towork-in-process (“WIP”) mix, resource availability changes, associatework schedule and skill sets (e.g., “queue-jumping” hot lots, specialwork requests, etc.) to meet the requirements of a “just-in-time”environment.

Stated more broadly, a measurement of process efficiency can be definedby how quickly demands by requesting tasks are satisfied through theallocation of process resources. Today, even though human operatorsassist in the allocation of resources to requesting tasks, decisions toallocate such resources are controlled by management (whether humanmanagement based upon periodic reports (e.g., daily, weekly, monthly or,even, quarterly), or automated management based upon periodic batcheddata, or some combination of the two) which reacts or decides based uponstale data, rather than reacting/deciding dynamically.

Therefore, a further need exists for a process system and relatedgraphical user interface through which management reacts timely relativeto conventional systems based upon dynamic data.

SUMMARY OF THE INVENTION

To address the above-discussed deficiencies of the prior art, it is aprimary object of the present invention to provide systems, as well asmethods of operating the same, for allocating multi-function resourcesamong a plurality of tasks within a process system.

Broadly, such systems and methodologies enable real-time processautomation through mathematical modeling of multi-function processresources (e.g., manufacturing tools, hardware, software, databases,communication/connectivity resources, transportation resources,facilities, utilities, inventories, etc.), and then allocating ones ofsuch resources to perform various tasks within the process system,commonly in accord with at least one application process. It should benoted that such systems and methodologies may be suitably arranged tomaintain a knowledge database and to modify the same to record pastexperiences thereby enabling the same to be self-learning.

In accord with the principles of the present invention, an exemplaryresource allocator is introduced that allocates such multi-functionresources among a plurality of tasks within the process system executingthe at least one application process. This resource allocator comprisesa monitoring controller, a model of the process system and a resourceallocation controller.

An exemplary monitoring controller monitors measurable characteristicsassociated with the executing application process, multi-functionresources and related tasks, each of the measurable characteristicsbeing one of a status characteristic and a logistical characteristic. Anexemplary model represents mathematically the multi-function resourcesand the tasks, and defines relationships among related ones thereof as afunction of the application process (e.g., one or more applicationprocesses, resources, tasks, etc.). An exemplary resource allocationcontroller operates the model in response to the monitored measurablecharacteristics and allocates ones of the multi-function resources amongones of the tasks within the process system to efficiently execute theat least one application process.

In a related embodiment, a suitably arranged graphical user interface(“GUI”) is associated with the process system. The GUI is operable totransform real-time process system information into multimedia format toenable supervisor (i.e., human management, system management(self-learning or otherwise), or some suitable combination of human andsystem management) interaction.

An advantageous embodiment for the present invention is a resourceallocator for use in a diffusion process. For instance, a diffusionprocess in semiconductor wafer fabrication may be described as a processof depositing a dopant material onto a silicone substrate and diffusingthe dopant material into the silicone substrate via thermal agitation(the diffusion process is preferably capable of executing a plurality ofdiffusion process plans).

An exemplary resource allocator operates to allocate a plurality ofmulti-function resources, or tools (e.g., furnaces (high temperatureatmospheric pressure, low pressure chemical vapor deposition, doping(bbr3, pocl3, etc.), anneal, alloy, curing, etc.)); wet chemical processstations (self contained, open bath, etc.); work in process controllers(stockers, transport modules, etc.); people (equipment loaders,operators, repair technicians, etc.), among a plurality of tasks of anygiven diffusion process plan. The resource allocator comprises amonitoring controller, a model and resource allocation controller.

The monitoring controller monitors measurable characteristics associatedwith an executing diffusion process plan, the multi-function resources,and the related tasks. Each of the measurable characteristics is one ofa status characteristic (e.g., execution data, timing data, alert data,completion data, recipe name, sub-recipe name, idle or running, etc.) ora logistical characteristic (e.g., assignment data, availability data,capacity data, diffusion process plan data, prioritization data, processduration, queue time, alternative resource options, competing resourceoptions, skill sets, etc.).

The model is of the diffusion process, and represents mathematically theplurality of multi-function resources and the plurality of tasks, aswell as defines relationships among related ones thereof as a functionof the diffusion process plans.

The resource allocation controller operates the diffusion process modelin response to the monitored measurable characteristics and allocatescertain of the multi-function resources among certain of the tasks toefficiently execute the diffusion process plan. The resource allocationcontroller is therefore operable to select and reselect allocated onesof the multi-function resources.

During the diffusion process, meaning before, during and betweenexecution of various diffusion process plans, the resource allocationcontroller operates to modify ones of the mathematical representationsin response to the status or logistical characteristic data. In arelated embodiment, the resource allocator comprises a data repositoryhaving at least a knowledge database, and the resource allocator furtheroperates to modify the knowledge database in response to changes to orthe condition/value of the status and logistical characteristic data tothereby enable the resource allocator to be self-learning.

Before undertaking a DETAILED DESCRIPTION OF THE INVENTION, it may beadvantageous to set forth a definition of certain words and phrases usedthroughout this patent document: the terms “include” and “comprise,” aswell as derivatives thereof, mean inclusion without limitation; the term“or,” is inclusive, meaning and/or; the phrases “associated with” and“associated therewith,” as well as derivatives thereof, may mean toinclude, be included within, interconnect with, contain, be containedwithin, connect to or with, coupled to or with, be communicable with,cooperate with, interleave, juxtapose, be proximate to, be bound to orwith, have, have a property of, or the like; the term “memory” means anystorage device, combination of storage devices, or part thereof whethercentralized or distributed, whether locally or remotely; and the terms“controller,” “processor” and “allocator” mean any device, system orpart thereof that controls at least one operation, such a device, systemor part thereof may be implemented in hardware, firmware or software, orsome combination of at least two of the same.

It should be noted that the functionality associated with any particularcontroller or allocator may be centralized or distributed, whetherlocally or remotely. In particular, a controller or allocator maycomprise one or more data processors, and associated input/outputdevices and memory that execute one or more application programs and/oran operating system program.

Additional definitions for certain words and phrases are providedthroughout this patent document, those of ordinary skill in the artshould understand that in many, if not most instances, such definitionsapply to prior, as well as future uses of such defined words andphrases.

The foregoing has outlined rather broadly the features and technicaladvantages of the present invention so that those skilled in the art maybetter understand the detailed description of the invention thatfollows. Additional features and advantages of the invention will bedescribed hereinafter that form the subject of the claims of theinvention. Those skilled in the art should appreciate that they mayreadily use the conception and the specific embodiment disclosed as abasis for modifying or designing other structures for carrying out thesame purposes of the present invention. Those skilled in the art shouldalso realize that such equivalent constructions do not depart from thespirit and scope of the invention in its broadest form.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present invention, and theadvantages thereof, reference is made to the following descriptionstaken in conjunction with the accompanying drawings, wherein likenumbers designate like objects, and in which:

FIG. 1 illustrates an exemplary process system and associated resourceallocator in accordance with the principles of the present invention;

FIG. 2A illustrates a graphical user interface (“GUI”) in accord withthe principles of the present invention for use in a semiconductor waferfabrication;

FIG. 2B illustrates an icon from the GUI of FIG. 2A that represents oneof a plurality of multi-function resources in accord with the principlesof the present invention for use in a semiconductor wafer fabrication;

FIG. 3 illustrates a block diagram of a process system implemented as aninformation management system associated with the resource allocator ofFIG. 1, all in accordance with the principles of the present invention;

FIG. 4 illustrates a block diagram of a network infrastructure utilizedto implement a distributed embodiment of the process system of FIGS. 1and 3 in association with a centralized implementation of resourceallocator, all in accordance with the principles of the presentinvention;

FIG. 5 illustrates a flow diagram of an exemplary method of operatingthe process system of FIGS. 1 to 4 in accordance with the principles ofthe present invention; and

FIG. 6 illustrates a conceptual block diagram of an exemplary embodimentof a resource allocator for use in a diffusion process in semiconductorwafer fabrication according to one embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIGS. 1 through 6, discussed below, and the various embodiments used todescribe the principles of the present invention in this patentdocument, are by way of illustration only and should not be construed inany way to limit the scope of the invention. Those skilled in the artwill understand that the principles of the present invention may beimplemented in any suitably arranged system, as well as method ofoperating the same, for allocating a plurality of resources, bothprocess and human resources, among a plurality of tasks within a processsystem.

Turning initially to FIG. 1, illustrated is an exemplary process system(generally designated 100, that includes a plurality of applicationprocesses 105; for purposes hereof, “application process” is definedbroadly as a program or a part of a program that can execute, whetherindependently of other parts or not, and is designed for or to meet theneeds of the process system 100—an application process may suitablyconsist of low-, mid- or high- level programs or parts thereof thatinteract with process system 100) that is associated with a resourceallocator (generally designated 110), all in accordance with theprinciples of the present invention. For purposes hereof, the phrase“process system” means any computer processing system, network ofcomputer processing systems, or portion thereof that is operable tomonitor, control or otherwise supervise a process (e.g., informationmanagement system, manufacturing plant (e.g., semiconductorfabrication), refinery, hotel, restaurant, traffic control,transportation control, emergency services (e.g., police, fire, medical,military, etc.), and the like).

According to one advantageous embodiment hereof, process system 100 is asemiconductor fabrication facility that is operable to handle multipleand varied application processes, or plans, associated with complexmulti-function resources (e.g., tools (including varying technologies))and tasks to manufacture multiple and widely varying semiconductorproducts. System 100 may, in whole or in part, be a network-based,real-time, visualized, intelligent (i.e., self-learning) system, andinclude control enhancements for industries, whether manufacturing orotherwise, that require timely delivery of services, products or otherresources.

Exemplary resource allocator 110 is operable to allocate a plurality ofmulti-function resources 115 among a plurality of tasks 120 withinprocess system 100, wherein, for purposes of illustration, exemplarymulti-function resources 115 may suitably be any tool, device or othersystem used in the manufacture process of semiconductor products.According to one advantageous embodiment hereof, resource allocator 110is a general processor that is operable to accept variable servicerequests and to intelligently apply the required resource(s) to addresssuch requests. Resource allocator 110 illustratively includes a memory125, a monitoring controller 130, a resource allocation controller 135and is associated with a graphical user interface (“GUI,” which providesgraphical information controls, as discussed with reference to FIGS. 2Aand 2B) 140, which cooperatively offer enhancements of real-time,visual, intelligent, and control functions, possibly through web-baseconnectivity.

Exemplary memory 125 is operable to store a model 145 of process system100. Exemplary model 145 represents mathematically application processes105, multi-function resources 115, and tasks 120, and also definesvarious relationships among related ones of application processes 105,multi-function resources 115, and tasks 120. According to oneadvantageous embodiment hereof, memory 125 includes a plurality ofdatabases (shown in FIG. 3) used, for instance, for service/function,control and knowledge.

A service/function database may be operable to store informationregarding customers, networks, transactions, resources, communicationsor the like. A control database may be operable to store algorithms,rules, key elements for decision-making or the like. A knowledgedatabase may be operable to provide task related intelligent informationto help make optimal decisions, and to acquire and accumulate experiencethrough evaluating results (i.e., artificial intelligence, expert systemanalysis, neural networks, etc.).

Exemplary monitoring controller 130 is operable to monitor measurablecharacteristics associated with ones of application processes 105,multi-function resources 115, and tasks 120. According to oneadvantageous embodiment hereof, monitoring controller 130 is a real-timemonitor of updated status or logistical data of resources and tasks, andenables human interaction online with other subsystems, allowing a humaninterface to respond to, modify, update or over-ride the automateddecision-making processes. Each of the measurable charactertistics isone of a status characteristic or a logistical characteristic.

Exemplary resource allocation controller 135 is responsive to ones ofthe monitored measurable characteristics and may be operable to: (i)operate the model; (ii) modify ones of the mathematical representationsof application processes 105, multi-function resources 115, tasks 120,and the defined relationships among related ones of applicationprocesses 105, multi-function resources 115, and tasks 120; and (iii)allocate ones of resources 115 among ones of tasks 120 within processsystem 100.

According to one advantageous embodiment hereof, broadly, resourceallocation controller 135 allocates ones of multi-function resources 115among ones of tasks 120 within process system 100 in response to themonitored measurable characteristics to efficiently execute one or moreapplication processes 105, and, more specifically, operates to interactwith available resources and tasks to generate and manage the requiredtransactions within one or more application processes 105 (noting, forinstance, that measurable characteristics of resource allocationcontroller 135 may be associated with management of customers, networks,resources, and communications, such as service objectives, metrics, andmeasurements).

Exemplary GUI 140 is a user interface that is operable to transformreal-time process system information into an audio or visual format toenable supervisory interaction. According to one advantageous embodimenthereof, GUI 140 is operable to visualize the data and status of externalresources, service requests as well as on-going transactions by usinggraphic displays, multimedia equipment to provide real-time data as wellas historical and statistical information with human interaction.

Turning to FIG. 2A illustrated is an exemplary GUI 140 in accord withthe principles of the present invention for use in a semiconductor waferfabrication. GUI 140 includes a plurality of icons 200 representing aplurality of multi-function resources 115. In wafer fabrication, themission is to provide the shortest cycle time, highest quality, costeffective products on time to continually meet revenue growth plans.This causes an on-going need to continuously improve manufacturingprocesses including the content and methods of delivering information toan operations staff.

Status information about the manufacturing tools and work in processinventory are often critical to making decisions needed to successfullyoperate a wafer manufacturing line on a daily basis. In executing anapplication process, or plan, it is critical to know what is plannednext—a time-consuming communication exercise. These plans may beflexible in responding to WIP mix, tool availability changes, associatedwork schedules and skill sets—a “just in time” environment is responsiveto “queue jumping hot lots”, or “Static WIP” as well as special workrequests for certain portions of lots that make the planning processmore difficult. Being able to project output by the “end of business”makes for its own special status requirements when attempting to measureturns and operational outputs.

Real-time information is preferred to updated batch reporting, and whencombined with GUI 140 interface, operational staff productivityincreases significantly. In one implementation, resource, or tool-level,status data is updated automatically every minute while the logisticalinformation is update every other minute. The exemplary running wheelicon is easily contrasted between “on” and “off” (or static) used todisplay an “idle” furnace making for quick interpretation.

According to this implementation, status data changes as the tool itselfprogresses through process sub-steps, and is sensed from the sensors,timers, controllers (e.g., mass flow controllers, thermocouples,countdown buffers, etc.), etc. Status data may suitably be modified byone resource or tool at a time and changes in logistical data do notdirectly cause a change in status data. Logistical data is typicallydigital in nature and arguably comprehends conditions not residing onthe resource or tool itself (e.g. number of lots, operatoridentification, plan state, etc.). The logistical data of a group ofresources or tools may change based on a status change of any oneresource or tool, a task, an application process, a lot of material, orthe like.

Many resources, such as furnaces, for example, can be sub-divided intosmaller logical workgroups arrangements or into process focus areagroups (e.g., clean oxidation). An exemplary display for each tube'sinformation is a combination of tool and logistical level data in astandardized format that includes:

-   -   tool name, tool focus Area assignment, idle or running, up or        down, ownership (e.g., Prod, Eng, Mnt), process running        including the sub-routine level, time remaining, time of        completion, # wafers in process, # wafers available to process,        # wafers in next application process (or plan), next process        planned, originator of next application process, rank of next        application process in relation to dispatching system.

Turning to FIG. 2B, illustrated is an exemplary icon that represents oneof a plurality of multi-function resources 115 in accord with theprinciples of the present invention for use in a semiconductor waferfabrication. Additional features include special symbols that appear ifthe tool develops an equipment error condition, as this may cause a needfor a modification of a loading plan, as an example. Buttons enablequeries of the factory logistical data including qualificationschedules, last “X” hour history, whole area WIP (e.g., running, readyto load, ready to pre-clean, etc.), application processes for othertools including the unload schedules for work currently in process.Button bars may also include launch points for viewing either thecurrent run data itself or in combination with historical runs of thisor any other furnace, according to this example.

Turning next to FIGS. 3 and 4, introduced is an information managementsystem embodiment of process system 100 of FIG. 1. Exemplary processsystem 100 is introduced by way of illustration only to describe theprinciples of the present invention and should not be construed in anyway to limit the scope of the invention. Illustrated is a conceptualblock diagram of process system 100 associated with a service operationresource allocator 110, all in accordance with the principles of thepresent invention. Exemplary process system 100, in addition to serviceoperation resource allocator 110, also includes a plurality ofapplication processes 105, namely, a service customer block, and aservice management block.

Exemplary service customer block may be a person or a controller; forinstance, service customer block may suitably be a person using acomputer that is associated with an intranet or the Internet, or it maybe an intelligent input/output device associated with equipment to sendand receive data using connectivity.

Exemplary service management block includes a plurality of GUIs 140 thatprovide user interfaces operable to transform real-time information intoan audio or visual format to enable supervisory interaction. Servicemanagement block is operable to enable supervisory interaction withflexibility to visualize and control the entire service process flexibly(in a related embodiment, such supervisory interaction may suitably bein detail or in general with zoom in/out functions in a real-time mode).

Exemplary service operation block 110 is a resource allocator that isoperable to allocate a plurality of service resources 115 among aplurality of tasks 120 within process system 100. Service resources 115include multifunction resources, which may include definitions of humanresources based upon services, functions, activities, skills,qualifications, task preferences, track records and the like. Exemplaryhuman resources may include service staff that work with customers orservice requests, such as waiters, mechanics, plumbers, painters,electricians, soldiers, technicians, engineers, etc. Exemplary humanresources may also include service coordinators, system operators andadministrators that support the operations, such as accountants,purchase agents, auditors, receptionists, secretaries, controllers,servicemen, network administrators, etc. Exemplary human resources mayalso include service managers, system managers, and operation managersthat manage the process system and make business and operationsdecisions, such as it managers, police chiefs, hotel managers,restaurant managers, store managers, officers, executives, etc.

The process resources may suitably be classified into eight categories,namely, tools, hardware, software, databases, communication/connectivityresources, transportation resources, facilities, utilities, andinventories. Exemplary hardware resources include computers, networkdevices such as switches/routers/hubs, digital/analog sensors, cables,meters, monitors, scopes, audio/video devices, special service tools,etc. Exemplary software resources include operation systems, networksystems, database systems, application programs, graphics interfaces,system utilities, special applications such as artificial intelligence,neural net, system control and data acquisition, etc.

Exemplary data resources include three databases, namely, (i) servicedatabases 210 that maintains service objects (customers/equipment),service transactions, networks, resources, and communications, (ii)control databases 220 that maintains key attributes, algorithms,instructions, mathematics and rules that manage, monitor and control theoperations, and (iii) knowledge databases 225 that maintain on-goingreal-time knowledge, information and experiences compiling for resourceretention and self-learning process.

Exemplary communication/connectivity resources include local-area andwide-area networks, Internet, telephones/facsimile, mail, etc. Exemplarytransportation resources include trucks, cars, boats, airplanes, bikes,motorcycles, railroads, space shuttles, balloons, military vehicles,all-terrain vehicles, satellites, etc. Exemplary technology resourcesinclude service automation technology that combines major technologyareas, namely, (i) network technologies in office automation, (ii) humanmachine interface (“HMI”) technologies in industrial automation, and(iii) artificial intelligent technologies. Exemplary facilitiesresources include computer control/monitor/server rooms, labs,workrooms, offices, towers/antenna, machines/tools, piping, etc.Exemplary utilities resources include electricity, water, fuel, air,chemicals, automated warehousing, distribution systems/gatheringsystems, etc. Exemplary inventory resources include supplies, materials,peripherals, components, ammunition, etc.

An important aspect of the illustrated embodiment is that serviceoperation block 110 provides systematic operation with automatic andresponsive control of service activities based on real-time service dataand built-in intelligent decisions from model 145 of FIG. 1. Routinedecisions are made by service automation while service operations are ongoing. The management is able, via GUIs 140, to make responsivedecisions and allocate or utilize service intelligently based on thereal-time graphics-enhanced information.

Service operation block 110 is illustratively associated with aplurality of service resources 115 and a plurality of service controls205. Exemplary service resources 115 may suitably include tools,hardware, software, information or facilities, all of which are to beapplied to service activities. Exemplary service controls 205 maysuitably include monitoring controller 130, resource allocationcontroller 135, and model 145, all of FIG. 1, that work cooperatively toautomatically issue service instructions according to defined rules ofmodel 145.

Service control 205 therefore monitors and controls the service resourceallocation and utilization as well as service level and matrix for theservice operation. Model 145 of service control 205 again representsmathematically service customer 105, service resources 115, and tasks120, and also defines various relationships among related ones of thesame, and includes a service database 210, a control database 220 andknowledge database 225. Any suitably arranged mathematicalrepresentation may be used for model 145 or, for that matter, any of themeasurable characteristics. Those skilled in the art will readilyrecognize that such mathematical representations will often beapplication dependent. Such measurable characteristics may be eitherstatus characteristics and logistical characteristics, and are used toexecute model 145 to efficiently allocate resources.

Exemplary service database 210 is operable to store real-timeinformation regarding service customers 105 and service activities.Service database 210 provides information of service activities toservice resources 115 through a plurality of service queues 216. Servicedatabase 210 also feeds real-time information to control database 220.According to the present embodiment, service database 210 may suitablybe a relational database with flat file structure containing data in atwo-dimensional table format. Exemplary control database 220 is operableto store consolidated real-time key attributes of information fromservice database 210 and also stores pre-defined algorithms(instructions and rules associated with monitoring controller 130 andresource allocation controller 135). Instructions can be automaticallyexecuted according to the rules and real-time key attributes. Servicecontrol 205 works with control database 220 to carry out definedinstructions. According to the present embodiment, control database 220is a data file with special format that contains key data and algorithms(instructions and rules associated with monitoring controller 130 andresource allocation controller 135).

Exemplary knowledge database 225 is operable as a central repository ofqualitative and quantitative information to develop standards ofperformance in activities that are common regardless of industry.Knowledge data that would serve as a reference point for performance andprocedural improvement to provide task related intelligent informationused to make decisions optimally, and to acquire and accumulateexperience through evaluating results (i.e., artificial intelligence,expert system analysis, neural networks, etc.).

An important aspect of the illustrated embodiment is that controldatabase 220 serves to provide information service management withmultimedia, and control enhancements based on real-time information. Insummary, using service database 210, control data base 220 and knowledgedatabase 225, resource allocator 110 is operable to allocate a pluralityof multifunction service resources 115 among a plurality of tasks withinprocess system 100.

Turning now to FIG. 4, illustrated is a conceptual block diagram of anexemplary network infrastructure utilized to implement a distributedembodiment of process system 100 in association with a centralizedimplementation of service operation resource allocator 110. Exemplarydistributed process system 100 includes a plurality of applicationprocesses 105, including LAN users 300, intelligent devices 305 (e.g.,personal data assistants (“PDAs”), two-way messaging devices, etc.), WANusers 310, Internet users 315, and the like. Those of ordinary skill inthe art will recognize that this embodiment and other functionallyequivalent embodiments may suitably be implemented by a variety ofmethods using many different computer, or processing, system platforms.Conventional computer and processing system architecture is more fullydiscussed in Computer Organization and Architecture, by WilliamStallings, MacMillan Publishing Co. (3^(rd) d. 1993); conventionalprocessing system network design is more fully discussed in Data NetworkDesign, by Darren L. Spohn, McGraw-Hill, Inc. (1993); and conventionaldata communications is more fully discussed in Data CommunicationsPrinciples, by R. D. Gitlin, J. F. Hayes and S. B. Weinstein, PlenumPress (1992) and in The Irwin Handbook of Telecommunications, by JamesHarry Green, Irwin Professional Publishing (2^(nd) ed. 1992). Each ofthe foregoing publications is incorporated herein by reference for allpurposes.

Broadly, process system 100 allocates a plurality of multifunctionresources among a plurality of tasks thereby enabling real-time processautomation through mathematical modeling of the process resources 115and tasks 120, and then allocating ones of such resources 115 to performvarious tasks 120 within the process system 100. For the purposes of theillustrated embodiment of FIG. 4, tasks are divided into threecategories, namely, service requests, service dispatches and informationsharing. A service request may suitably be stored in service databases210 with priority, location, contents, requirements, contacts, etc. Aservice dispatch may suitably be stored in control databases 220 andknowledge databases 225 with service level objectives, servicemetrics/measurements, transaction/actions, status and situations,decision-making processes with real-time responsive, pre-defined,programmed, intelligent, knowledge/experience retention andself-learning characters. Information sharing is a request for computergenerated audio/video and print report, e-based, real-time,graphical/visualized, etc.

Turning next to FIG. 5, illustrated is a flow diagram (generallydesignated 500) of an exemplary method of operating process system 100of FIGS. 1 to 4, all in accord with the principles of the presentinvention. For purposes of illustration, concurrent reference is made toembodiment disclosed with reference to FIG. 1. It is beneficial toassume that process system 100 is instantiated and fully operational,and for illustrative purposes directed to a raw material refiningenvironment. Further, for simplicity, assume that there are a plethoraof multifunction resources, including human resources. Thus, exemplaryprocess system 100 controls processing raw materials, and likelycontrols a control center and associated process stages (not shown;e.g., application processes 105).

A first multi-function resource 115 might include raw material grindersthat receive a feed of raw material and grind the same, such as by usinga pulverizer or a grinding wheel, into smaller particles of rawmaterial. A second process stage multi-function resource 115 mightinclude a washer that receives the ground raw materials and cleans thesame to remove residue from the first stage. A third multi-functionresource 115 might include separators that receive the ground, washedraw materials and separate the same into desired minerals and anyremaining raw materials. Since this process system and related facilityare provided for purposes of illustration only and the principles ofsuch a facility are well known, further discussion of the same is beyondthe scope of this patent document and unnecessary.

To begin, resource allocator 110 stores a model 145 of process system100 in memory (process step 505), model 145 representing mathematicallymultifunction resources 115, the process resources, the applicationprocesses 105 (i.e., the control for the grinders, separators andwashers, etc.), and relationships among related ones thereof. Resourceallocator 110 then monitors these measurable characteristics andreceives service requests (process step 510), and, for the presentexample, from a particular grinder. The measurable characteristics maybe status or logistical.

In response to measurable characteristics causing a request for serviceof the subject grinder, resource allocator 110 evaluates the alternateresources available and allocates one to provide the same function,along with process resources that may be necessary and appropriate tocomplete the same (process step 515). Resource allocator 110, inresponse to the servicing of the task, modifies ones of the mathematicalrepresentations, first indicating that the resource is occupied andpossibly indicating the quality with which the task was completed(process step 520).

According to the illustrated embodiment, resource allocator 110 modifiesknowledge database 225 to provide updated task related information tohelp make future decisions concerning the grinder, the allocatedalternative grinder, and possibly any human resource used to service thesame, etc., both intelligently and optimally. Resource allocator 110thereby acquires and accumulates experience through evaluating results(i.e., artificial intelligence, expert system analysis, neural networkanalysis, etc.). Thus, in a later scenario, should this samemultifunction resource 115 be otherwise occupied with another task andthis grinder requires a similar service, resource allocator 110 cansuitably utilize dynamic knowledge database 225 evaluate availableresources 115 to decide whether to reallocate this same grinder resource115 to the based upon past experience recorded in the associatedmeasurable characteristics or to allocate another resource to the taskleft uncompleted. Again, multifunction resources, both process andhuman, are re-usable, re-directable for “next” requests throughintelligent decision making sub-process of experience accumulation,analysis, optimization and self-learning. Knowledge database 225operates as a central repository of knowledge data, capturingqualitative and quantitative information to develop standards ofperformance in activities that are common regardless of industry.

Turning to FIG. 6, illustrated is a conceptual block diagram of anexemplary embodiment of a resource allocator 610 for use in a diffusionprocess 605 in semiconductor wafer fabrication 600. The diffusionprocesses in semiconductor wafer fabrication are well known and, for thepurposes hereof, may again be described as a process of depositing adopant material onto a silicone substrate and diffusing the dopantmaterial into the silicone substrate via thermal agitation.

According to the illustrated embodiment, diffusion process 605 isoperable to execute a plurality of diffusion process plans. Resourceallocator 610 operates to allocate a plurality of multi-functionresources or tools among a plurality of tasks of any given diffusionprocess plan. Resource allocator 610 comprises a monitoring controller620, resource allocation controller 625, a model 630, and a graphicaluser interface 640.

Exemplary monitoring controller 620 monitors measurable characteristicsassociated with an executing diffusion process plan, the multi-functionresources, and the related tasks. Each of the measurable characteristicsis one of a status characteristic or a logistical characteristic.Exemplary model 630 is of diffusion process 605, and representsmathematically the plurality of multi-function resources and theplurality of tasks, as well as defines relationships among related onesthereof as a function of the diffusion process plans.

Exemplary resource allocation controller 625 operates the diffusionprocess model 630 in response to the monitored measurablecharacteristics and allocates certain of the multi-function resourcesamong certain of the tasks to efficiently execute the diffusion processplan. Resource allocation controller 625 is therefore operable to selectand reselect allocated ones of the multi-function resources among onesof the tasks in response to the monitored measurable characteristics.

During the diffusion process, meaning before, during and betweenexecution of various diffusion process plans, resource allocationcontroller 625 operates to modify ones of the mathematicalrepresentations in response to the status or logistical characteristicdata.

The illustrated resource allocator 610 also comprises a data repository,or memory 615, having at least a knowledge database 635. Resourceallocator 610 further operates to modify knowledge database 635 inresponse to changes to or the condition/value of the status andlogistical characteristic data to thereby enable the resource allocatorto be self-learning.

In operation, resource allocator 610 allocates the multi-functionresources among the tasks within diffusion process 605 that executes oneor more diffusion process plans. Initially, and continuously, monitoringcontroller 620 monitors measurable characteristics that are associatedwith an at least one executing diffusion process plan, themulti-function resources, and the tasks. Each of the measurablecharacteristics is either status a characteristic or a logisticalcharacteristic.

Model 630 of diffusion process 605 is instantiated to mathematicallyrepresent the of multi-function resources and tasks of diffusion process605, and to define relationships among related ones thereof as afunction of the at least one diffusion process plan.

Resource allocation controller 625 operates model 630 in response to themonitored measurable characteristics, and allocates ones of themulti-function resources among ones of the tasks within diffusionprocess 605 to efficiently execute at least one diffusion process plan.

Although the present invention has been described in detail, thoseskilled in the art should understand that they can make various changes,substitutions and alterations herein without departing from the spiritand scope of the invention in its broadest form.

1. A resource allocator operable to allocate a plurality ofmulti-function resources among a plurality of tasks within a processsystem, said process system capable of executing at least oneapplication process, said resource allocator comprising: a monitoringcontroller that monitors measurable characteristics associated with saidat least one application process, said plurality of multi-functionresources, and said plurality of tasks, wherein each of said measurablecharacteristics comprises one of: a status characteristic and alogistical characteristic; a model of said process system representingmathematically said plurality of multi-function resources and saidplurality of tasks, and defining relationships among related onesthereof as a function of said at least one application process; and aresource allocation controller that operates said model in response toones of said monitored measurable characteristics and allocates ones ofsaid plurality of multi-function resources among ones of said pluralityof tasks within said process system to efficiently execute said at leastone application process.
 2. The resource allocator as set forth in claim1 wherein said resource allocation controller is operable to modify oneor more mathematical representations in the model.
 3. The resourceallocator as set forth in claim 1 further comprising a graphical userinterface that is operable to enable supervisory interaction.
 4. Theresource allocator as set forth in claim 1 further comprising a datarepository having at least a knowledge database, said resource allocatoroperable to modify said knowledge database in response to ones of saidmonitored measurable characteristics thereby enabling said resourceallocator to be self-learning.
 5. The resource allocator as set forth inclaim 1 wherein said resource allocation controller is operable toreselect one of said allocated ones of said plurality of multi-functionresources among ones of said plurality of tasks within said processsystem in response to said monitored measurable characteristics.
 6. Amethod of operating a resource allocator to allocate a plurality ofmulti-function resources among a plurality of tasks within a processsystem, said process system capable of executing at least oneapplication process, said method of operating said resource allocatorcomprising the steps of: monitoring measurable characteristics with amonitoring controller, said measurable characteristics associated withsaid at least one application process, said plurality of multi-functionresources, and said plurality of tasks, wherein each of said measurablecharacteristics comprises one of: a status characteristic and alogistical characteristic; representing mathematically said plurality ofmulti-function resources and said plurality of tasks within a model ofsaid process system, and defining relationships among related onesthereof as a function of said at least one application process; andoperating said model in response to ones of said monitored measurablecharacteristics, and allocating ones of said plurality of multi-functionresources among ones of said plurality of tasks within said processsystem using a resource allocation controller to efficiently executesaid at least one application process.
 7. The method of operating theresource allocator as set forth in claim 6 further comprising the stepof providing a graphical user interface operable to enable supervisoryinteraction.
 8. The method of operating the resource allocator as setforth in claim 6 further comprising the step of modifying one or moremathematical representations in the model.
 9. The method of operatingthe resource allocator as set forth in claim 7 wherein the resourceallocator further comprises a data repository having at least aknowledge database, and said method further comprises the step ofmodifying said knowledge database in response to ones of said monitoredmeasurable characteristics thereby enabling said resource allocator tobe self-learning.
 10. The method of operating the resource allocatorresource allocator as set forth in claim 7 further comprising the stepof reselecting one of said allocated ones of said plurality ofmulti-function resources among ones of said plurality of tasks withinsaid process system in response to said monitored measurablecharacteristics.
 11. A process system capable of executing at least oneapplication process, said process system comprising: a plurality ofprocess subsystems; a plurality of tasks to be performed within saidplurality of process subsystems; a plurality of multi-functionresources; and a resource allocator that is operable to allocate saidplurality of multi-function resources among said plurality of tasks,said resource allocator comprising: a monitoring controller thatmonitors measurable characteristics associated with said at least oneapplication process, said plurality of multi-function resources, andsaid plurality of tasks, wherein each of said measurable characteristicscomprises one of: a status characteristic and a logisticalcharacteristic; a model of said process system representingmathematically said plurality of multi-function resources and saidplurality of tasks, and defining relationships among related onesthereof as a function of said at least one application process; and aresource allocation controller that operates said model in response toones of said monitored measurable characteristics, and allocates ones ofsaid plurality of multi-function resources among ones of said pluralityof tasks within said process system to efficiently execute said at leastone application process.
 12. The process system as set forth in claim 11wherein said resource allocation controller is operable to modify one ormore mathematical representations in the model.
 13. The process systemas set forth in claim 11 further comprising a graphical user interfacethat is operable to enable supervisory interaction.
 14. The processsystem as set forth in claim 11 further comprising a data repositoryhaving at least a knowledge database, said resource allocator operableto modify said knowledge database in response to ones of said monitoredmeasurable characteristics thereby enabling said resource allocator tobe self-learning.
 15. The process system as set forth in claim 11wherein said resource allocation controller is operable to reselect oneof said allocated ones of said plurality of multi-function resourcesamong ones of said plurality of tasks within said process system inresponse to said monitored measurable characteristics.
 16. The processsystem as set forth in claim 13 wherein said process system controls oneof a manufacturing plant, a refinery, a hotel, a restaurant, a trafficcontrol system, a transportation control system and an emergencyservices system.
 17. The process system as set forth in claim 13 whereinsaid resource allocator is an information management system.
 18. Aresource allocator operable to allocate a plurality of multi-functionresources among a plurality of tasks within a diffusion process, saiddiffusion process capable of executing at least one diffusion processplan, said resource allocator comprising: a monitoring controller thatmonitors measurable characteristics associated with said at least onediffusion process plan, said plurality of multi-function resources, andsaid plurality of tasks, wherein each of said measurable characteristicscomprises one of: a status characteristic and a logisticalcharacteristic; a model of said diffusion process representingmathematically said plurality of multi-function resources and saidplurality of tasks, and defining relationships among related onesthereof as a function of said at least one diffusion process plan; and aresource allocation controller that operates said model in response toones of said monitored measurable characteristics and allocates ones ofsaid plurality of multi-function resources among ones of said pluralityof tasks within said diffusion process to efficiently execute said atleast one diffusion process plan.
 19. The resource allocator as setforth in claim 18 wherein said resource allocation controller isoperable to modify one or more mathematical representations in themodel.
 20. The resource allocator as set forth in claim 18 furthercomprising a graphical user interface that is operable to enablesupervisory interaction.
 21. The resource allocator as set forth inclaim 18 further comprising a data repository having at least aknowledge database, said resource allocator operable to modify saidknowledge database in response to ones of said monitored measurablecharacteristics thereby enabling said resource allocator to beself-learning.
 22. The resource allocator as set forth in claim 18wherein said resource allocation controller is operable to reselect oneof said allocated ones of said plurality of multi-function resourcesamong ones of said plurality of tasks within said diffusion process inresponse to said monitored measurable characteristics.
 23. The resourceallocator as set forth in claim 18 wherein each said statuscharacteristic is one of execution data, timing data, alert data,completion data.
 24. The resource allocator as set forth in claim 18wherein each said logistical characteristic is one of assignment data,availability data, capacity data, diffusion process plan data,prioritization data.
 25. A method of operating a resource allocator toallocate a plurality of multi-function resources among a plurality oftasks within a diffusion process, said diffusion process capable ofexecuting at least one diffusion process plan, said method of operatingsaid resource allocator comprising the steps of: monitoring measurablecharacteristics with a monitoring controller, said measurablecharacteristics associated with said at least one diffusion processplan, said plurality of multi-function resources, and said plurality oftasks, wherein each of said measurable characteristics comprises one ofa status characteristic and a logistical characteristic; representingmathematically said plurality of multi-function resources and saidplurality of tasks within a model of said diffusion process, anddefining relationships among related ones thereof as a function of saidat least one diffusion process plan; and operating said model inresponse to ones of said monitored measurable characteristics, andallocating ones of said plurality of multi-function resources among onesof said plurality of tasks within said diffusion process using aresource allocation controller to efficiently execute said at least onediffusion process plan.
 26. The method of operating a resource allocatoras set forth in claim 25 further comprising the step of modifying one ormore mathematical representations in the model.
 27. The method ofoperating a resource allocator as set forth in claim 25 wherein saidresource allocator comprises a graphical user interface that is operableto enable supervisory interaction.
 28. The method of operating aresource allocator as set forth in claim 25 wherein said resourceallocator comprises a data repository having at least a knowledgedatabase, said resource allocator operable to modify said knowledgedatabase in response to ones of said monitored measurablecharacteristics thereby enabling said resource allocator to beself-learning.
 29. The method of operating a resource allocator as setforth in claim 25 further comprising the step of reselecting one of saidallocated ones of said plurality of multi-function resources among onesof said plurality of tasks within said diffusion process in response tosaid monitored measurable characteristics.
 30. The method of operating aresource allocator as set forth in claim 25 wherein each said statuscharacteristic is one of execution data, timing data, alert data,completion data.
 31. The method of operating a resource allocator as setforth in claim 25 wherein each said logistical characteristic is one ofassignment data, availability data, capacity data, diffusion processplan data, prioritization data.